Leveraging Localisation Techniques for In-Network Duplicate Event Data Detection and Filtering

Abstract

Event detection has become a ubiquitous application in the domain of wireless sensor networks. In any distributed event detection system, duplicate event data that can increase the likelihood of network congestion is a primary concern, and in-network data aggregation is a popular approach to alleviate this problem; similarly, duplicate data can be discarded. We propose a novel approach that utilises localisation techniques to quickly identify and discard duplicates among event reports. Using just the locations of nodes reporting events, the proposed classifier is able to make a decision on which event reports are to be discarded as duplicates. We show that our approach has the potential to greatly reduce packet load in a network and thus save energy and increase sensor life.